Sort by
Refine Your Search
-
Country
-
Employer
- CNRS
- Argonne
- Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID
- Bar Ilan University
- Gran Sasso Science Institute
- IMT Atlantique
- Lawrence Berkeley National Laboratory
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- National Renewable Energy Laboratory NREL
- Nature Careers
- Oak Ridge National Laboratory
- Okinawa Institute of Science and Technology
- Purdue University
- Technical University of Munich
- University of Amsterdam (UvA)
- University of Miami
- University of Minnesota
- University of Oregon
- 8 more »
- « less
-
Field
-
, Teamwork, Safety, and Service Basic Qualifications: A Ph.D. degree in Mathematics, Computer Science, Physics, Chemistry, Engineering, or a related discipline. A strong foundation in linear algebra (tensor
-
geometry, connecting algebraic combinatorics, algebraic geometry, and high-energy physics . We invite applications for postdoctoral positions to join this interdisciplinary program. Successful candidates
-
PyTorch. ✔️ You have a good knowledge of linear algebra and statistics. ✔️ You have good listening, analysis and synthesis skills, and are curious and open-minded. ✔️ You are adaptable, autonomous, rigorous
-
in high performance scientific computing, multi-linear algebra and tensor contractions for heterogeneous exascale architectures. The successful candidate will join the NumPEx PEPR to reinforce
-
, applied mathematics, physics, computer science, computational topology, or a related quantitative discipline. A strong foundation in algebraic topology and/or differential geometry (e.g., homology theory
-
foundations and principles of Machine Learning, Linear Algebra (vectorial and matricial operations, optimization), with a particular focus on Neural Networks (pytorch), 3) problem solving skills, 4) familiarity
-
calculus, linear algebra, probability and statistics, and possess strong proficiency in mathematical thinking and abstract reasoning. Cellular, biochemical, molecular experimental skills Experience working
-
development spanning areas such as optimization, Fourier analysis, numerical linear algebra, statistics, machine learning, and high-performance computing for one or more of the following: (1) reconstruction
-
clusters, cloud computing, or GPU acceleration. Strong mathematical background in linear algebra, probability, and statistics. Prior research experience with publications or preprints. The University
-
linear algebra, numerical methods for PDEs and dynamical systems, stochastic methods in statistical mechanics, hydrodynamic limits, interacting many-body systems, quantum macroscopic evolution equations